Open source language and environment for analysis, statistics & visualization
Use data set “mpg” (provided with R): Fuel economy data from 1999 and 2008 for 38 popular models of car
# list the structure of mpg
str(mpg)
Classes 'tbl_df', 'tbl' and 'data.frame': 234 obs. of 11 variables:
$ manufacturer: chr "audi" "audi" "audi" "audi" ...
$ model : chr "a4" "a4" "a4" "a4" ...
$ displ : num 1.8 1.8 2 2 2.8 2.8 3.1 1.8 1.8 2 ...
$ year : int 1999 1999 2008 2008 1999 1999 2008 1999 1999 2008 ...
$ cyl : int 4 4 4 4 6 6 6 4 4 4 ...
$ trans : chr "auto(l5)" "manual(m5)" "manual(m6)" "auto(av)" ...
$ drv : chr "f" "f" "f" "f" ...
$ cty : int 18 21 20 21 16 18 18 18 16 20 ...
$ hwy : int 29 29 31 30 26 26 27 26 25 28 ...
$ fl : chr "p" "p" "p" "p" ...
$ class : chr "compact" "compact" "compact" "compact" ...
# print mpg
mpg
# A tibble: 234 x 11
manufacturer model displ year cyl trans drv cty hwy
<chr> <chr> <dbl> <int> <int> <chr> <chr> <int> <int>
1 audi a4 1.8 1999 4 auto(l5) f 18 29
2 audi a4 1.8 1999 4 manual(m5) f 21 29
3 audi a4 2.0 2008 4 manual(m6) f 20 31
4 audi a4 2.0 2008 4 auto(av) f 21 30
5 audi a4 2.8 1999 6 auto(l5) f 16 26
6 audi a4 2.8 1999 6 manual(m5) f 18 26
7 audi a4 3.1 2008 6 auto(av) f 18 27
8 audi a4 quattro 1.8 1999 4 manual(m5) 4 18 26
9 audi a4 quattro 1.8 1999 4 auto(l5) 4 16 25
10 audi a4 quattro 2.0 2008 4 manual(m6) 4 20 28
# ... with 224 more rows, and 2 more variables: fl <chr>, class <chr>
# help on mpg
?mpg
R functions
A function is a set of statements organized together to perform a specific task. Arguments control how the function is used.
# help on plotting function ggplot
?ggplot
Create a new ggplot
ggplot() initializes a ggplot object. It can be used to declare the input data frame for a graphic and to specify the set of plot aesthetics intended to be common throughout all subsequent layers unless specifically overridden.
Usage
ggplot(data = NULL, mapping = aes(), …, environment = parent.frame())
ggplot(data = mpg) + geom_point(mapping = aes(x=displ,y=hwy),size=8) +
theme_bw(base_size = 40)
ggplot(data = mpg) + geom_point(mapping = aes(x=displ,y=hwy),size=8) + geom_smooth(mapping = aes(x=displ,y=hwy)) +
theme_bw(base_size = 40)
ggplot(data = mpg) + geom_point(mapping = aes(x = displ, y = hwy, color = class), size = 6) +
theme_bw(base_size = 40)
ggplot(data = mpg) + geom_point(mapping = aes(x=displ,y=hwy), size = 6) + facet_wrap(~class, nrow = 2) + theme_bw(base_size = 40)
ggplot(data = mpg) + geom_point(mapping = aes(x=displ,y=hwy, color = manufacturer=="subaru"), size = 6) +
facet_wrap(~class, nrow = 2) +
labs(title = "Modify plot labels, title, legend", x = "engine displacement [l]", y = "highway [mpg]") +
theme_bw(base_size = 40) +
scale_colour_manual(values=c("#000000", "#FF0000"),name="Subaru") + theme(legend.justification=c(1,0), legend.position=c(1,0))
Grossman-Clarke S. et al. 2017. International Journal of Climatology 37(2): 905–917, doi: 10.1002/joc.4748.
Grossman-Clarke S. et al. 2017. International Journal of Climatology 37(2): 905–917, doi: 10.1002/joc.4748.
Grossman-Clarke S. et al. 2017. International Journal of Climatology 37(2): 905–917, doi: 10.1002/joc.4748.
RStudio is an integrated development environment (IDE) for R.
Three steps for installing RStudio
Download the binary setup file for R for your operating system
Open the downloaded file .exe (windows) or .pkg (macosx) and install following instructions
Download the free Desktop R Studio version here: http://www.rstudio.com/products/rstudio/download/
READY! OPEN R Studio by clicking on the prompt!
What is an R-package?
Packages are collections of R functions, example data, and compiled code.
Choose mirror: RStudio -> Preferences -> Packages
Menu -> Tools -> Install packages
From main R menu choose:
Tools -> Check for package updates
In order to use a package it needs to be loaded in each new R session via console or included in a script:
# load package (use pound key for comments)
library(ggplot2)
# print information on installed packages
sessionInfo()
R version 3.3.2 (2016-10-31)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: macOS Sierra 10.12.5
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] dplyr_0.7.0 purrr_0.2.2.2 readr_1.1.1 tidyr_0.6.3
[5] tibble_1.3.3 ggplot2_2.2.1 tidyverse_1.1.1 knitr_1.16
loaded via a namespace (and not attached):
[1] Rcpp_0.12.11 highr_0.6 cellranger_1.1.0 plyr_1.8.4
[5] forcats_0.2.0 tools_3.3.2 digest_0.6.12 jsonlite_1.5
[9] lubridate_1.6.0 evaluate_0.10 gtable_0.2.0 nlme_3.1-131
[13] lattice_0.20-35 rlang_0.1.1 psych_1.7.5 parallel_3.3.2
[17] haven_1.0.0 xml2_1.1.1 stringr_1.2.0 httr_1.2.1
[21] hms_0.3 grid_3.3.2 glue_1.0.0 R6_2.2.1
[25] readxl_1.0.0 foreign_0.8-68 reshape2_1.4.2 modelr_0.1.0
[29] magrittr_1.5 scales_0.4.1 assertthat_0.2.0 mnormt_1.5-5
[33] rvest_0.3.2 colorspace_1.3-2 labeling_0.3 stringi_1.1.5
[37] lazyeval_0.2.0 munsell_0.4.3 broom_0.4.2
For a complete list of functions, use:
# print help on package "stat"
library(help = "stats")
Micrometeorological site data in *.csv format from the Central-Arizona Phoenix LTER as available from the EDI repository
tutorial_dat<-read.csv('data1_r_intro.csv')
# print structure of data set "tutorial_dat"
str(tutorial_dat)
'data.frame': 3290 obs. of 41 variables:
$ TIMESTAMP : Factor w/ 3290 levels "2015-07-09 13:00:00",..: 1 2 3 4 5 6 7 8 9 10 ...
$ RECORD : int 0 1 2 3 4 5 6 7 8 9 ...
$ VW_Avg : num 0.412 0.411 0.411 0.413 0.414 0.415 0.415 0.415 0.414 0.413 ...
$ VW_2_Avg : num 0.42 0.421 0.421 0.422 0.422 0.422 0.423 0.423 0.424 0.424 ...
$ VW_3_Avg : num 0.298 0.298 0.298 0.298 0.298 0.298 0.298 0.298 0.298 0.298 ...
$ AirTC_Avg : num -28 35.9 37.2 37.8 38 ...
$ RH_Avg : num 13 30.8 27.7 26 25 ...
$ AirTC_2_Avg : num -11.1 35.6 36.8 37.4 37.7 ...
$ RH_2_Avg : num 16.2 29.3 26.5 24.9 24.2 ...
$ AirTC_3_Avg : num -21.9 35.5 36.3 36.9 37.1 ...
$ RH_3_Avg : num 13.7 27.8 25.6 24.2 23.4 ...
$ PPFin_Avg : num 2218 1611 1969 1601 1773 ...
$ ndvi_Jenkins_Avg : num 0.516 0.501 0.505 0.515 0.525 0.534 0.541 0.551 0.553 0.551 ...
$ ndvi_Huemmrich_Avg : num 0.539 0.531 0.533 0.547 0.551 0.559 0.564 0.575 0.579 0.579 ...
$ ndvi_Wilson_Avg : num 0.492 0.477 0.481 0.492 0.501 0.51 0.518 0.527 0.529 0.527 ...
$ evi2_Avg : num 0.325 0.318 0.333 0.335 0.343 0.352 0.36 0.373 0.378 0.373 ...
$ Rain_mm_Tot : num 0 0 0 0 0 0 0 0 0 0 ...
$ Temp_C_Avg : num 30.4 30.7 30.5 30.9 31.3 ...
$ PTemp_C_Avg : num 38.8 38.9 39 40.7 41.8 ...
$ shf_Avg : num 4.42 7.79 8.95 10.89 11.63 ...
$ BP_mbar_Avg : int 951 962 962 962 961 961 960 960 960 960 ...
$ Batt_Volt_Min : num 12.8 12.8 12.8 12.9 12.9 ...
$ short_up_Avg : num 985 725 893 732 826 ...
$ short_dn_Avg : num 187 136 174 134 151 ...
$ long_up_Avg : num -96.8 -87.8 -106.8 -99.1 -100.4 ...
$ long_dn_Avg : num 27.86 4.62 22.46 21.89 25.06 ...
$ cnr4_T_C_Avg : num 38.2 36.9 38.1 38.6 38.5 ...
$ long_up_corr_Avg : num 436 436 426 436 435 ...
$ long_dn_corr_Avg : num 561 528 555 557 560 ...
$ Rs_net_Avg : num 798 589 719 598 675 ...
$ Rl_net_Avg : num -124.7 -92.5 -129.3 -121 -125.4 ...
$ albedo_Avg : num 0.187 0.175 0.192 0.177 0.18 ...
$ Rn_Avg : num 673 496 590 477 550 ...
$ TT_C : num 36 37.3 38.2 37.4 37.2 ...
$ SBT_C : num 37.2 35.8 37.3 37.5 38.3 ...
$ wnd_dir_compass_Avg: num 0 1.32 237.32 237.27 228.37 ...
$ Rainfall : num 0 0 0 0 0 0 0 0 0 0 ...
$ H : num NA NA 186 249 203 ...
$ LE : num NA NA 171 137 154 ...
$ C : num NA NA 0.0571 0.0822 0.0252 ...
$ G_calc : num 4.42 7.7 8.95 11.05 11.72 ...
# print variable AirTC_Avg of data set "tutorial_dat"
tutorial_dat$AirTC_Avg
[1] -28.010 35.890 37.160 37.770 38.040 38.500 38.290 38.060
[9] 37.700 37.210 36.640 35.910 35.380 34.600 33.750 33.030
[17] 32.250 31.530 29.910 28.280 27.400 28.570 27.970 24.900
[25] 21.750 23.120 23.150 23.040 22.930 23.060 22.090 20.050
[33] 21.370 20.720 21.690 23.420 25.450 25.390 26.600 29.920
[41] 32.550 33.850 34.620 35.390 36.200 36.400 36.600 37.130
[49] 37.940 37.100 38.480 38.940 38.180 38.420 38.930 38.920
[57] 38.180 38.200 37.200 36.500 35.720 35.190 34.560 33.890
[65] 33.190 32.600 31.910 31.340 30.590 30.380 29.590 28.020
[73] 26.930 26.830 26.490 26.750 26.930 26.970 26.820 25.780
[81] 25.220 25.070 25.960 27.610 28.960 30.130 31.670 32.580
[89] 34.110 35.300 35.830 36.510 37.140 37.460 38.300 38.760
[97] 38.940 38.960 39.770 39.500 40.150 40.030 40.070 40.120
[105] 40.080 40.020 38.960 38.410 37.630 36.560 35.350 34.780
[113] 34.360 33.400 32.350 32.110 31.610 29.150 27.500 25.070
[121] 21.840 21.920 22.510 23.870 23.770 23.990 22.600 20.550
[129] 20.210 20.560 21.250 21.430 24.040 25.760 26.230 29.450
[137] 31.670 32.810 33.850 35.800 37.160 37.610 38.710 38.010
[145] 38.180 38.950 38.970 38.720 39.940 40.730 41.080 41.070
[153] 41.400 40.870 39.670 38.400 37.730 36.830 35.220 32.280
[161] 30.850 31.480 33.350 32.790 31.770 31.540 31.080 30.830
[169] 30.830 30.380 30.650 30.010 29.230 28.550 27.960 27.320
[177] 26.720 26.630 27.340 28.150 29.840 30.810 32.190 33.730
[185] 34.770 36.730 38.250 38.840 39.220 40.040 39.960 40.670
[193] 40.890 40.820 41.710 41.720 42.170 42.130 42.340 42.260
[201] 41.950 41.730 40.690 40.580 40.070 39.240 38.300 37.140
[209] 36.220 34.530 33.440 32.300 30.930 31.070 31.150 28.610
[217] 29.310 31.020 30.840 30.740 30.400 29.900 27.060 25.860
[225] 26.280 26.860 27.280 27.940 28.510 27.560 27.080 31.150
[233] 33.320 35.240 36.950 37.570 38.810 39.320 39.540 39.660
[241] 40.010 40.770 41.050 41.840 41.660 41.420 41.550 41.790
[249] 40.840 40.130 39.350 38.970 37.930 35.890 34.780 32.650
[257] 31.990 31.320 32.770 32.670 32.350 31.870 31.210 30.780
[265] 30.790 30.310 30.140 30.040 29.930 29.730 29.190 29.030
[273] 28.740 28.550 28.070 27.840 28.720 30.350 32.380 32.450
[281] 32.870 33.970 35.740 36.580 37.820 38.290 38.560 39.280
[289] 39.700 40.000 39.800 40.510 40.560 40.730 40.960 40.900
[297] 40.530 40.230 39.610 38.910 38.300 37.460 35.380 33.670
[305] 34.250 34.190 33.080 32.750 33.730 33.330 33.310 31.880
[313] 30.440 30.620 30.270 29.640 29.740 29.960 29.310 28.340
[321] 27.970 28.060 27.480 27.820 29.310 30.640 32.390 33.740
[329] 35.020 36.400 36.930 38.210 38.670 39.790 39.680 40.330
[337] 40.310 40.750 41.020 41.230 41.830 41.610 42.590 42.650
[345] 42.310 41.810 40.940 40.050 39.270 38.100 36.120 33.510
[353] 32.030 31.260 32.470 32.800 32.660 32.200 31.010 28.000
[361] 27.210 28.190 28.410 28.060 27.530 27.110 25.740 23.140
[369] 23.580 23.580 23.740 25.050 27.040 28.050 29.040 29.960
[377] 29.990 30.810 31.700 32.380 34.810 36.240 34.900 36.430
[385] 35.550 36.110 38.410 37.770 38.280 37.590 37.140 36.290
[393] 36.340 35.410 34.810 34.610 34.320 33.750 32.680 32.960
[401] 32.930 32.730 31.960 31.090 29.910 29.470 28.530 27.710
[409] 27.240 26.560 26.610 26.570 26.270 26.060 25.870 25.300
[417] 24.880 24.940 24.840 25.540 26.420 27.270 28.950 30.700
[425] 31.390 32.090 33.320 34.380 34.930 35.550 37.330 37.920
[433] 38.080 37.700 38.210 39.180 38.920 36.900 35.330 32.850
[441] 31.980 31.350 31.260 30.980 30.680 30.760 28.970 28.890
[449] 28.080 26.750 25.550 24.670 24.780 25.040 24.730 24.350
[457] 23.740 23.580 23.460 23.320 23.330 23.590 23.830 23.370
[465] 23.330 23.600 23.320 23.350 23.910 24.600 25.540 27.130
[473] 28.670 30.630 31.300 32.960 33.330 32.770 34.320 34.700
[481] 36.000 34.930 35.310 34.730 35.200 36.380 37.290 37.410
[489] 36.860 35.670 34.060 33.910 33.910 33.390 32.490 31.880
[497] 31.420 30.590 29.850 29.700 30.080 28.680 27.160 27.360
[505] 27.290 26.230 25.790 25.550 24.820 24.280 24.050 24.320
[513] 24.660 24.520 24.390 25.960 28.720 29.990 31.790 32.240
[521] 33.340 34.080 33.630 34.100 35.210 36.100 36.290 37.340
[529] 38.230 37.890 38.230 38.310 38.590 38.700 39.070 39.150
[537] 38.770 38.340 37.750 37.120 36.300 35.520 34.520 33.220
[545] -0.965 -78.050 -78.130 -78.150 -78.150 -78.170 -78.170 -78.190
[553] -78.200 -78.210 -78.200 -78.200 -78.200 -78.220 -78.210 -78.240
[561] -78.230 -78.250 -78.200 -78.220 -78.170 -78.150 -78.130 -78.090
[569] -78.020 -77.980 -77.930 -77.860 -77.900 -77.910 -77.850 -77.680
[577] -77.700 -77.710 -77.720 -77.790 -77.810 -77.820 -77.760 -77.780
[585] -77.770 -77.720 -77.800 -77.850 -77.880 -77.910 -77.960 -78.000
[593] -13.130 31.690 30.700 30.100 29.480 29.440 28.920 30.430
[601] 30.640 28.680 29.010 27.950 26.290 25.470 25.400 25.210
[609] 25.480 24.450 23.110 22.960 25.190 28.250 30.940 32.800
[617] 32.750 34.820 35.530 36.370 37.360 37.520 38.350 38.410
[625] 39.110 39.500 39.590 40.120 40.250 40.030 40.570 40.280
[633] 40.030 39.760 39.550 38.830 38.200 37.210 35.280 33.310
[641] 32.280 31.370 31.710 32.900 31.630 29.850 28.130 27.640
[649] 27.430 28.170 29.690 28.790 28.370 27.110 25.240 24.580
[657] 23.670 23.320 23.360 24.260 25.290 26.710 29.360 31.760
[665] 33.030 34.700 34.850 35.660 35.950 37.630 37.900 38.460
[673] 37.820 38.950 39.350 39.510 39.450 39.510 38.870 39.810
[681] 39.870 39.350 38.520 37.680 37.250 36.680 35.790 35.500
[689] 32.760 32.160 32.100 31.370 30.660 30.310 29.970 28.080
[697] 26.910 27.740 28.000 28.470 28.610 28.610 27.290 25.860
[705] 27.030 27.300 27.460 27.500 27.980 27.420 26.880 28.680
[713] 29.970 31.040 32.580 33.880 34.650 34.980 35.040 36.720
[721] 37.240 38.460 39.110 38.970 39.810 40.270 40.060 40.310
[729] 40.090 39.910 38.970 38.280 37.840 36.610 35.440 33.880
[737] 31.290 29.900 29.560 29.520 29.170 28.100 27.060 26.680
[745] 25.900 25.820 25.510 25.150 25.420 26.120 26.660 26.790
[753] 26.630 26.750 26.990 27.560 28.810 28.970 30.090 31.490
[761] 33.780 34.050 35.470 36.190 37.940 36.910 38.440 39.390
[769] 40.350 41.300 41.670 42.410 41.500 40.710 41.730 41.710
[777] 40.530 40.720 40.870 40.130 38.890 37.010 33.750 31.110
[785] 30.760 30.360 29.440 29.990 30.750 29.150 28.070 25.160
[793] 20.990 21.050 22.290 22.920 22.710 22.940 21.630 19.630
[801] 20.880 21.640 22.190 23.130 25.430 25.580 27.020 30.470
[809] 33.970 36.450 37.910 39.040 39.810 40.290 40.390 41.170
[817] 42.000 41.520 42.460 41.630 42.380 42.100 42.400 41.040
[825] 40.720 39.950 39.470 39.070 38.510 38.180 37.140 35.770
[833] 35.280 34.250 32.590 29.810 28.270 27.990 28.700 28.290
[841] 28.360 27.940 27.050 27.110 26.540 25.840 25.610 25.170
[849] 24.500 24.510 24.230 24.920 26.680 28.990 30.960 32.820
[857] 34.690 36.620 37.810 37.810 37.880 38.270 38.790 39.820
[865] 40.370 40.430 40.590 40.880 40.830 41.480 41.490 41.120
[873] 41.550 41.100 40.670 39.710 38.640 37.200 35.140 33.450
[881] 32.160 31.750 30.230 29.490 29.440 30.400 29.820 28.770
[889] 28.520 27.450 27.700 28.230 29.690 28.680 26.650 23.900
[897] 23.650 24.100 24.730 25.100 25.700 26.380 25.820 28.750
[905] 31.740 33.780 35.460 35.530 36.790 37.870 38.880 40.600
[913] 41.140 40.260 41.080 40.330 41.540 41.660 39.630 39.090
[921] 38.870 38.740 38.370 38.060 37.260 36.850 35.950 34.690
[929] 33.720 32.740 31.820 31.140 30.240 29.840 29.580 28.950
[937] 28.700 28.630 29.180 28.910 28.410 27.720 27.390 27.220
[945] 27.290 26.900 27.290 27.740 29.020 29.690 30.020 30.280
[953] 30.830 31.710 32.320 33.630 33.590 33.970 35.180 34.790
[961] 35.980 36.880 36.920 37.460 37.800 39.040 38.230 38.880
[969] 38.520 38.460 37.690 36.870 36.840 34.230 31.600 30.520
[977] 30.580 30.220 29.770 29.800 29.500 29.260 28.400 27.820
[985] 27.630 27.510 27.210 27.060 26.780 27.140 27.490 27.010
[993] 26.750 26.190 25.680 25.750 26.350 27.740 30.410 32.700
[1001] 33.830 35.940 37.170 37.410 38.140 39.480 39.700 39.760
[1009] 40.080 40.310 40.230 40.980 40.400 40.450 40.490 40.130
[1017] 40.230 40.050 39.710 38.930 37.930 36.610 34.900 32.280
[1025] 30.960 30.690 30.490 30.370 30.430 30.220 29.900 27.990
[1033] 25.880 25.560 25.810 26.720 27.600 27.730 26.010 24.050
[1041] 24.490 24.440 24.470 25.660 28.060 29.920 28.740 30.600
[1049] 33.470 36.460 37.960 37.920 39.660 39.900 40.140 41.250
[1057] 41.280 40.590 40.920 42.680 39.820 37.880 35.760 34.340
[1065] 34.020 32.920 28.180 28.010 28.450 27.490 25.710 25.810
[1073] 26.180 25.810 26.180 26.840 26.790 27.110 26.950 26.930
[1081] 26.780 26.630 26.870 26.590 26.450 26.380 26.300 26.500
[1089] 26.600 26.750 26.620 26.040 28.380 29.680 30.590 31.380
[1097] 32.490 33.820 34.730 36.130 37.350 38.150 39.090 38.480
[1105] 38.500 38.790 38.880 39.410 39.360 39.400 39.490 39.060
[1113] 39.130 39.120 38.620 37.990 37.210 36.250 34.490 33.020
[1121] 31.650 31.180 30.590 30.220 29.950 30.050 30.510 27.730
[1129] 26.750 28.500 28.790 28.650 28.890 28.470 26.930 24.630
[1137] 25.550 25.180 25.410 25.270 27.070 28.190 29.040 31.510
[1145] 34.170 36.460 37.710 38.150 38.870 40.040 40.400 39.980
[1153] 40.360 40.710 41.380 41.140 41.170 41.730 41.310 41.950
[1161] 41.210 41.120 40.950 40.020 38.800 37.260 34.320 32.520
[1169] 31.550 30.830 30.540 30.430 29.810 29.230 29.370 29.040
[1177] 28.520 28.360 27.800 27.280 26.180 26.300 26.280 26.580
[1185] 26.900 27.180 26.920 27.160 28.210 30.150 32.290 34.230
[1193] 35.420 36.820 38.610 39.970 40.820 40.910 41.190 42.710
[1201] 41.810 41.860 42.080 42.730 42.580 43.390 42.810 42.260
[1209] 42.310 42.480 42.380 41.050 39.810 37.960 36.250 33.710
[1217] 31.660 30.610 29.790 29.100 28.530 27.910 27.970 26.950
[1225] 22.620 22.680 23.830 25.860 25.480 25.690 24.750 21.810
[1233] 21.510 22.290 22.760 24.240 26.140 26.770 27.680 30.740
[1241] 34.370 37.150 38.190 38.940 40.120 40.580 42.510 42.080
[1249] 41.670 42.620 42.340 42.610 42.900 42.880 43.520 43.600
[1257] 43.410 43.090 42.780 41.600 40.070 38.770 35.950 32.830
[1265] 31.550 30.910 30.560 29.710 28.750 28.610 27.940 27.310
[1273] 26.920 26.790 26.700 26.480 26.010 25.520 25.150 24.920
[1281] 24.710 24.170 23.980 24.160 25.820 28.910 31.520 34.060
[1289] 35.760 37.830 39.030 39.150 40.130 40.770 41.310 42.440
[1297] 42.810 42.810 42.800 43.670 43.650 44.560 43.700 43.800
[1305] 43.510 43.200 42.830 41.730 40.870 39.720 37.650 34.900
[1313] 33.200 31.870 31.300 30.380 30.160 29.810 29.200 29.340
[1321] 29.500 29.460 30.290 30.280 29.960 30.710 30.540 29.280
[1329] 28.710 29.550 29.480 30.690 31.800 32.020 33.190 33.380
[1337] 33.060 33.490 35.080 35.660 37.750 38.080 38.700 38.140
[1345] 37.870 37.990 38.260 40.730 40.340 40.850 41.390 42.010
[1353] 41.480 40.910 40.020 38.500 36.290 34.030 32.490 31.360
[1361] 30.440 29.990 29.030 29.270 29.120 28.680 28.940 27.150
[1369] 23.460 23.770 24.700 25.440 26.460 26.840 25.500 23.000
[1377] 24.890 26.940 27.770 28.850 31.130 31.200 31.210 30.610
[1385] 30.540 32.260 32.710 36.240 38.090 39.760 38.880 39.340
[1393] 37.690 38.920 39.610 39.990 40.300 40.470 38.470 28.810
[1401] 27.490 27.520 29.050 29.350 29.070 27.350 25.240 25.380
[1409] 25.750 25.710 25.260 25.390 24.870 25.110 25.610 25.680
[1417] 25.700 25.670 25.430 25.410 25.350 24.970 24.710 24.740
[1425] 25.040 25.030 25.040 25.090 25.560 27.000 28.390 29.960
[1433] 31.550 33.950 35.110 35.560 36.360 37.280 37.820 37.600
[1441] 37.850 37.530 38.430 38.580 39.710 38.900 39.190 38.650
[1449] 38.500 38.570 37.200 35.850 34.660 33.510 31.620 30.830
[1457] 30.030 29.930 29.960 30.800 30.010 29.020 28.720 27.900
[1465] 25.140 25.650 25.600 25.750 26.650 27.120 26.240 24.110
[1473] 24.550 25.530 25.710 25.800 26.780 27.650 27.760 30.260
[1481] 32.810 35.030 36.540 38.330 38.790 39.180 38.790 39.610
[1489] 39.650 39.750 39.810 40.310 40.140 40.440 40.310 40.600
[1497] 40.380 40.400 39.990 39.390 38.280 36.170 33.780 32.930
[1505] 32.630 32.870 32.200 31.650 31.040 30.500 29.880 30.070
[1513] 30.110 29.940 30.770 30.200 28.990 28.250 28.320 28.410
[1521] 26.870 26.360 26.420 26.410 27.220 28.780 29.470 30.000
[1529] 31.050 34.270 34.200 34.800 37.730 38.220 38.730 38.720
[1537] 40.200 38.600 38.830 39.740 39.860 39.950 39.460 39.260
[1545] 39.200 39.010 38.630 37.840 37.200 36.460 35.580 33.690
[1553] 32.660 31.850 31.380 31.230 32.420 33.490 33.480 30.110
[1561] 26.020 26.700 28.340 28.660 28.730 29.090 27.350 24.970
[1569] 25.750 27.000 27.080 27.980 29.650 29.940 30.700 31.830
[1577] 33.530 33.530 28.920 26.520 25.090 26.180 27.730 28.720
[1585] 29.310 32.190 34.830 35.950 36.280 35.580 35.710 36.930
[1593] 38.040 37.930 36.610 36.310 34.780 33.410 32.010 31.600
[1601] 31.480 27.330 23.180 23.970 24.260 24.150 23.960 23.760
[1609] 24.450 25.280 25.460 25.330 25.370 25.380 25.110 25.280
[1617] 25.370 24.670 24.590 25.000 26.000 28.010 30.290 31.390
[1625] 33.130 34.590 36.020 36.890 38.430 39.570 39.590 40.860
[1633] 41.230 41.220 41.160 41.160 41.870 42.410 42.680 42.560
[1641] 41.850 40.500 39.280 38.990 38.320 35.790 34.690 34.190
[1649] 33.890 33.370 32.300 31.870 30.790 30.780 30.220 29.160
[1657] 28.450 28.200 28.350 27.980 27.390 26.910 26.450 26.190
[1665] 25.990 25.860 25.020 25.000 26.780 28.900 30.630 32.090
[1673] 33.770 34.950 36.480 38.240 39.260 40.930 41.400 42.800
[1681] 43.080 43.720 43.920 43.680 44.460 44.980 44.900 44.720
[1689] 44.010 43.400 42.820 42.300 40.930 38.530 35.590 34.890
[1697] 33.800 32.960 33.010 32.800 31.920 31.350 32.690 30.480
[1705] 26.960 28.430 30.040 30.690 30.860 30.690 28.390 26.120
[1713] 26.820 28.000 29.110 29.100 30.600 30.300 29.510 32.110
[1721] 34.560 36.470 38.790 40.380 41.700 42.030 42.310 43.050
[1729] 43.520 43.640 43.600 44.030 44.590 43.840 44.500 43.840
[1737] 42.230 43.050 42.420 40.980 39.180 38.920 38.090 37.300
[1745] 36.110 31.550 26.930 29.120 30.620 30.860 30.570 30.120
[1753] 29.920 29.920 29.660 29.160 28.710 28.260 28.130 27.840
[1761] 27.620 27.510 27.480 28.170 29.390 31.200 32.620 34.170
[1769] 35.800 36.890 38.420 39.540 39.920 40.840 40.470 41.500
[1777] 42.330 42.180 42.660 43.720 44.350 44.270 45.040 45.110
[1785] 44.580 44.800 44.400 43.320 41.730 39.090 36.480 35.130
[1793] 34.130 33.430 32.530 31.790 31.800 32.170 31.100 28.880
[1801] 25.040 26.180 27.920 28.750 30.540 32.720 30.750 26.480
[1809] 26.830 27.670 28.560 27.890 29.140 29.970 29.740 31.480
[1817] 33.970 35.530 37.100 38.710 39.940 40.640 41.560 41.150
[1825] 40.990 40.800 41.050 41.980 41.810 42.190 43.060 43.610
[1833] 43.110 42.390 41.960 42.190 41.460 40.240 38.470 35.840
[1841] 35.890 33.080 30.060 33.870 34.920 35.000 32.960 31.350
[1849] 31.160 31.270 30.400 29.790 29.710 30.370 31.080 29.910
[1857] 28.890 28.720 28.990 30.320 31.010 31.960 32.930 33.720
[1865] 34.290 35.140 36.310 38.280 39.560 40.030 39.900 38.820
[1873] 39.500 40.380 40.040 40.230 40.410 40.600 40.790 41.010
[1881] 40.810 40.790 40.510 40.010 39.320 38.460 37.000 37.010
[1889] 36.440 35.990 35.020 34.540 33.150 33.050 33.290 30.110
[1897] 27.250 27.010 26.580 26.860 26.750 26.400 25.160 23.120
[1905] 23.110 23.540 23.540 23.980 25.430 25.560 25.240 27.900
[1913] 30.840 32.820 34.620 36.160 37.020 37.110 37.540 37.850
[1921] 38.430 38.550 38.610 39.490 40.180 40.090 40.950 40.840
[1929] 40.970 40.240 39.710 38.650 37.700 36.750 35.610 34.560
[1937] 32.110 28.890 25.340 29.820 31.610 31.310 29.100 27.850
[1945] 27.720 27.610 26.750 26.270 25.880 25.220 24.940 24.870
[1953] 24.570 24.630 24.850 24.840 25.590 27.040 28.420 29.660
[1961] 31.310 33.090 35.090 37.300 38.340 38.110 38.250 39.140
[1969] 39.240 38.680 39.170 39.990 39.250 40.500 40.050 39.760
[1977] 39.100 39.150 39.150 38.410 36.870 34.500 32.550 31.520
[1985] 30.540 29.790 29.290 28.840 28.470 28.130 28.190 27.600
[1993] 27.040 26.520 26.710 26.130 25.980 25.960 25.560 25.080
[2001] 24.810 24.570 24.410 24.170 25.270 27.710 30.110 31.900
[2009] 33.420 34.570 36.030 37.520 37.960 39.010 39.310 39.630
[2017] 39.390 39.860 39.680 40.150 40.530 40.940 40.900 41.510
[2025] 40.850 40.680 40.090 39.200 37.980 36.740 35.810 34.820
[2033] 33.520 32.210 30.980 30.590 29.920 29.380 28.920 27.030
[2041] 23.790 25.060 25.860 25.850 25.800 25.380 24.630 22.990
[2049] 23.560 24.510 24.990 25.710 27.010 27.520 26.670 29.230
[2057] 31.500 33.760 35.120 36.110 36.540 37.480 37.770 38.490
[2065] 39.090 39.390 39.180 39.400 40.100 40.110 39.970 40.290
[2073] 39.990 39.770 39.840 38.530 37.280 35.750 34.880 33.700
[2081] 33.150 31.530 29.260 31.890 32.710 32.830 32.290 30.940
[2089] 31.490 31.850 30.340 35.860 36.910 38.010 39.010 39.620
[2097] 39.830 39.820 40.850 40.440 39.920 39.860 40.040 40.410
[2105] 40.860 39.540 39.600 39.340 39.010 37.890 35.490 33.900
[2113] 33.260 32.890 31.710 31.580 31.090 31.390 30.850 31.090
[2121] 32.770 30.270 27.910 28.660 28.770 28.260 28.140 28.260
[2129] 26.780 24.580 25.390 25.760 25.320 25.500 27.370 27.730
[2137] 26.850 28.820 30.720 33.090 33.460 34.300 37.790 36.830
[2145] 36.890 36.750 35.610 35.620 36.810 37.450 38.150 38.360
[2153] 37.170 36.120 36.060 34.050 27.310 27.330 27.120 27.370
[2161] 27.800 28.020 28.520 27.400 25.690 26.060 26.470 26.640
[2169] 27.010 27.680 27.200 26.920 26.130 25.420 25.270 25.040
[2177] 24.690 24.070 24.050 24.160 24.410 24.840 25.740 27.720
[2185] 28.970 30.140 32.170 34.540 36.160 37.010 38.200 38.760
[2193] 39.070 40.550 39.440 39.990 38.960 39.300 39.320 39.790
[2201] 39.770 40.000 39.500 38.850 38.300 37.540 36.500 35.250
[2209] 33.180 31.650 31.200 32.430 31.920 31.230 30.930 30.100
[2217] 29.730 30.520 30.160 29.370 28.590 28.130 28.690 27.810
[2225] 27.360 26.720 26.460 26.530 25.970 25.790 26.750 28.780
[2233] 30.900 32.650 34.090 36.000 37.910 39.130 39.620 40.320
[2241] 40.210 40.050 40.370 40.450 40.250 38.920 40.980 40.960
[2249] 40.400 37.370 36.870 34.310 28.630 27.510 28.560 29.400
[2257] 29.090 28.900 27.910 27.850 28.180 27.880 27.890 27.290
[2265] 26.040 24.770 22.490 22.420 22.920 23.200 23.540 23.430
[2273] 23.160 22.070 21.540 21.680 21.770 22.450 23.660 24.630
[2281] 25.550 28.360 30.540 33.390 35.730 36.490 37.480 38.450
[2289] 39.160 39.340 38.860 40.070 39.590 39.650 40.080 40.530
[2297] 40.700 40.770 40.740 40.330 39.690 38.920 37.890 35.750
[2305] 33.920 33.900 32.440 29.400 25.580 26.110 26.880 27.150
[2313] 27.410 27.060 26.930 26.210 26.490 26.550 26.600 26.580
[2321] 26.570 26.400 26.530 26.850 26.820 26.330 27.290 28.610
[2329] 30.400 32.500 34.540 36.620 38.470 39.750 40.570 41.010
[2337] 42.050 41.700 41.520 41.660 41.610 41.780 42.230 42.130
[2345] 42.450 42.060 41.970 41.490 40.660 39.030 37.500 36.340
[2353] 34.770 32.510 32.370 31.760 29.300 27.460 27.730 28.210
[2361] 28.410 27.550 25.870 25.420 24.940 24.920 24.620 24.800
[2369] 24.640 22.740 22.320 22.580 23.710 23.460 24.500 26.020
[2377] 26.840 29.700 32.690 35.540 36.090 36.690 39.060 38.490
[2385] 38.970 39.390 39.970 40.360 40.310 40.480 40.560 40.770
[2393] 40.770 40.720 40.500 40.120 39.200 37.950 36.580 35.750
[2401] 36.110 31.050 29.980 30.040 29.010 29.530 29.260 29.160
[2409] 29.310 28.760 27.840 27.160 26.750 26.570 27.050 26.370
[2417] 26.150 26.400 26.940 27.080 26.780 26.460 27.040 28.460
[2425] 29.400 30.700 32.840 35.230 37.290 37.750 38.760 38.330
[2433] 38.660 39.200 39.160 39.500 39.510 39.220 39.730 39.860
[2441] 39.890 39.970 39.650 39.280 38.230 37.780 35.460 33.170
[2449] 32.820 30.190 24.590 25.020 23.910 24.380 24.390 24.300
[2457] 24.430 24.370 24.310 24.530 24.590 24.470 24.270 24.070
[2465] 23.790 22.650 22.320 22.250 22.010 22.040 23.000 24.360
[2473] 25.640 27.430 29.110 30.920 32.280 33.680 34.390 35.410
[2481] 36.230 35.720 36.950 37.370 37.920 38.250 38.630 38.160
[2489] 37.480 37.180 36.770 36.190 34.880 33.120 31.810 30.400
[2497] 29.530 29.260 28.900 27.600 25.290 25.360 26.360 27.150
[2505] 28.620 29.310 28.630 28.320 28.220 28.690 28.500 28.100
[2513] 27.220 26.580 27.040 26.740 25.860 25.830 26.320 27.590
[2521] 28.780 31.010 32.450 33.840 34.090 33.880 34.910 35.820
[2529] 36.190 35.820 36.250 36.840 37.700 37.650 39.030 38.470
[2537] 38.510 36.760 36.150 36.950 36.680 35.190 33.400 31.520
[2545] 30.180 29.000 28.290 27.580 27.010 26.890 26.650 26.110
[2553] 26.190 26.490 25.760 25.340 25.730 26.310 26.330 26.890
[2561] 26.460 26.310 26.230 25.300 24.670 24.730 25.540 26.720
[2569] 28.210 30.040 31.850 34.300 34.360 36.310 36.980 37.240
[2577] 37.770 37.820 38.700 35.890 34.590 33.040 31.880 31.730
[2585] 33.780 33.600 33.340 29.810 28.250 27.470 26.640 25.990
[2593] 25.090 24.800 24.940 24.700 24.310 23.950 23.460 22.980
[2601] 22.550 22.040 21.500 20.790 20.560 20.540 21.090 20.990
[2609] 20.990 20.770 20.380 20.630 20.570 20.640 21.410 22.400
[2617] 22.960 25.210 27.640 30.060 32.000 33.060 34.070 35.030
[2625] 35.840 36.660 36.060 35.690 34.820 34.130 34.980 35.730
[2633] 35.110 34.170 33.670 33.110 32.540 31.890 31.190 31.010
[2641] 30.770 30.530 30.120 27.500 24.470 24.530 24.640 25.420
[2649] 25.430 25.020 24.970 24.830 24.580 24.530 23.940 23.630
[2657] 23.310 23.260 23.060 23.020 23.090 23.420 23.820 24.810
[2665] 25.880 27.170 27.670 28.780 29.690 29.890 30.510 30.870
[2673] 30.500 30.800 32.600 33.800 33.640 33.590 34.480 34.710
[2681] 35.250 33.220 34.210 33.970 32.640 31.930 30.260 29.240
[2689] 28.280 28.020 27.880 27.980 27.810 27.410 27.110 26.890
[2697] 25.830 24.730 22.990 22.440 22.790 23.600 23.970 23.980
[2705] 23.590 22.600 22.340 22.380 22.180 22.080 22.620 24.490
[2713] 25.900 28.540 30.840 32.900 34.570 35.890 36.340 37.380
[2721] 38.420 37.500 37.110 37.060 37.890 37.710 37.790 38.130
[2729] 38.090 37.510 37.450 37.180 36.060 35.260 33.500 31.050
[2737] 29.680 28.950 28.100 26.830 24.240 24.520 25.040 25.570
[2745] 25.590 25.440 25.100 24.790 24.520 24.620 24.470 24.110
[2753] 23.960 23.870 24.040 23.920 23.570 23.890 25.560 26.570
[2761] 27.800 28.660 28.920 30.630 31.130 31.600 32.560 31.970
[2769] 32.520 32.690 33.560 34.530 35.110 34.920 35.180 35.660
[2777] 36.110 36.650 36.110 35.260 34.380 33.450 32.150 29.930
[2785] 28.740 28.010 28.260 28.170 28.210 29.580 29.560 28.500
[2793] 28.520 27.220 23.990 24.680 25.670 26.270 26.160 26.410
[2801] 25.330 23.290 23.280 23.910 24.360 24.610 24.970 24.870
[2809] 23.650 25.630 29.240 33.050 35.120 34.860 33.830 33.910
[2817] 35.780 35.560 35.320 36.250 35.740 36.130 37.300 37.320
[2825] 37.620 37.590 37.440 37.080 36.500 35.070 32.500 32.060
[2833] 32.100 31.070 32.170 28.360 23.400 26.260 29.630 29.710
[2841] 29.560 28.980 27.770 27.790 27.740 26.720 26.390 25.820
[2849] 25.700 25.070 24.740 24.630 24.870 24.890 24.830 25.610
[2857] 26.890 28.470 30.100 31.760 33.150 33.010 32.410 32.720
[2865] 34.210 34.730 35.670 35.320 34.600 34.440 34.170 34.460
[2873] 34.800 34.110 33.770 33.730 33.710 32.810 31.900 30.320
[2881] 29.410 29.070 28.600 27.880 27.930 29.010 29.060 28.750
[2889] 27.940 26.960 26.710 27.490 28.310 27.910 27.840 27.130
[2897] 26.480 26.120 25.920 25.700 25.870 26.070 27.090 26.710
[2905] 27.370 28.550 29.170 29.970 30.390 30.730 31.830 32.080
[2913] 32.090 32.330 32.210 32.480 32.180 31.520 31.630 32.360
[2921] 31.880 31.440 31.060 30.360 29.490 28.380 27.260 26.410
[2929] 25.870 25.650 25.110 25.030 25.040 24.590 23.800 23.170
[2937] 22.940 22.850 22.550 21.620 21.210 21.100 20.980 20.850
[2945] 21.150 21.300 20.550 20.210 19.970 19.860 20.310 21.700
[2953] 23.280 24.280 26.320 29.480 31.910 33.140 33.940 34.550
[2961] 35.490 35.880 36.410 36.620 36.580 36.630 36.820 36.950
[2969] 37.330 37.230 36.920 36.680 36.060 34.770 32.170 30.190
[2977] 29.190 28.420 27.870 26.550 23.880 23.820 24.400 24.530
[2985] 24.250 24.340 23.960 23.740 23.710 23.890 23.490 23.370
[2993] 23.360 23.170 22.930 22.770 22.690 22.480 22.620 24.540
[3001] 26.960 28.800 30.570 33.550 35.650 37.060 37.760 38.520
[3009] 39.460 39.430 39.900 39.860 39.390 40.070 40.180 40.130
[3017] 39.750 40.070 39.800 39.320 38.730 36.970 35.480 33.910
[3025] 32.910 32.240 32.510 31.060 29.790 29.850 30.350 29.430
[3033] 28.600 26.540 23.410 23.320 24.570 25.040 25.220 27.400
[3041] 25.750 22.800 21.910 22.100 22.520 22.710 23.580 25.200
[3049] 24.460 27.460 30.710 32.480 35.090 35.840 36.200 37.050
[3057] 36.410 36.620 36.490 37.140 37.920 38.270 38.690 38.910
[3065] 39.320 39.230 38.750 38.070 36.970 35.190 34.000 32.800
[3073] 31.680 30.730 29.870 25.600 23.840 23.970 24.040 23.720
[3081] 23.430 23.520 23.630 23.540 23.860 23.460 23.110 22.820
[3089] 22.350 22.680 22.660 22.600 22.280 21.910 21.960 22.810
[3097] 24.100 25.400 27.020 30.140 32.940 34.970 35.820 37.130
[3105] 36.960 36.650 36.490 36.810 36.090 35.840 36.310 36.520
[3113] 36.640 36.380 35.110 33.990 34.460 33.180 31.470 30.340
[3121] 29.940 28.410 27.160 26.010 25.480 24.480 24.290 24.130
[3129] 24.330 24.280 23.280 23.010 23.320 26.070 26.620 26.420
[3137] 25.610 24.770 25.010 25.520 25.250 24.870 24.930 25.620
[3145] 26.110 28.190 29.630 29.770 30.630 31.040 32.400 32.550
[3153] 33.540 34.020 34.670 35.490 34.680 33.930 33.890 34.770
[3161] 35.260 35.750 35.380 34.700 33.710 32.740 30.200 27.400
[3169] 26.260 25.920 25.590 25.130 25.460 27.600 27.440 25.610
[3177] 24.010 22.530 21.530 21.130 21.080 21.030 21.000 20.930
[3185] 20.740 20.660 21.130 21.230 21.360 21.170 21.420 22.710
[3193] 25.190 27.200 28.840 31.200 33.300 34.400 34.190 34.690
[3201] 35.530 35.110 35.140 35.250 35.560 35.810 35.490 35.800
[3209] 35.870 35.590 35.360 34.910 33.920 32.390 30.650 28.810
[3217] 27.360 26.470 25.750 25.930 25.730 24.850 23.430 22.760
[3225] 22.440 22.080 22.270 21.890 21.100 20.760 20.250 19.560
[3233] 19.120 19.030 19.010 18.760 18.890 18.470 18.880 20.810
[3241] 23.580 26.260 28.400 30.880 33.310 34.560 35.180 36.010
[3249] 35.670 36.170 36.170 36.280 35.730 35.660 35.920 36.110
[3257] 36.330 35.930 35.730 35.000 34.240 32.690 30.290 29.020
[3265] 28.190 27.920 27.260 25.880 24.520 23.740 23.220 22.630
[3273] 22.080 21.780 20.230 19.650 19.830 20.130 19.670 19.300
[3281] 18.980 17.990 17.300 17.400 17.320 17.270 17.600 18.910
[3289] 21.210 24.170
ggplot(data=tutorial_dat)+geom_histogram(mapping = aes(x=AirTC_Avg,fill=Rainfall>0)) + theme_bw(base_size = 40)
# print variable AirTC_Avg of data set "tutorial_dat"
which(tutorial_dat$AirTC_Avg<(-10.))
[1] 1 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561
[18] 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578
[35] 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593
tutorial_dat$AirTC_Avg[546:593]
[1] -78.05 -78.13 -78.15 -78.15 -78.17 -78.17 -78.19 -78.20 -78.21 -78.20
[11] -78.20 -78.20 -78.22 -78.21 -78.24 -78.23 -78.25 -78.20 -78.22 -78.17
[21] -78.15 -78.13 -78.09 -78.02 -77.98 -77.93 -77.86 -77.90 -77.91 -77.85
[31] -77.68 -77.70 -77.71 -77.72 -77.79 -77.81 -77.82 -77.76 -77.78 -77.77
[41] -77.72 -77.80 -77.85 -77.88 -77.91 -77.96 -78.00 -13.13
tail(tutorial_dat$AirTC_Avg)
[1] 17.32 17.27 17.60 18.91 21.21 24.17
field<-read.csv('data2_r_intro.csv')
# print structure of data set "field"
str(field)
'data.frame': 807 obs. of 10 variables:
$ Longitude : num -112 -112 -112 -112 -112 ...
$ Latitude : num 33.1 33.1 33.1 33.1 33.1 ...
$ Fix.Type : int 2 2 2 2 2 2 2 2 2 2 ...
$ UTC.Time : int 182427 182427 182427 182427 182428 182428 182428 182428 182428 182429 ...
$ Logger.Time: int 136200 136400 136600 136800 137000 137200 137400 137600 137800 138000 ...
$ Config. : int 49 49 49 49 49 49 49 49 49 49 ...
$ Count : int 681 682 683 684 685 686 687 688 689 690 ...
$ NDVI : num 0.652 0.782 0.758 0.579 0.996 0.669 0.669 0.769 0.717 0.723 ...
$ NIR : num -0.0026 -0.0022 -0.0025 -0.002 -0.0025 -0.0024 -0.0014 -0.003 -0.0026 -0.0032 ...
$ Red : num 0 0 0 0 0 0 0 0 0 0 ...
ggplot(data=field)+geom_point(mapping = aes(x=Latitude,y=Longitude,color=NDVI), size=6)+scale_color_gradient(low="blue", high="yellow") + theme_bw(base_size = 40)